Browsing by Subject "Species distribution modeling"
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Item Open Access American chestnut (Castanea dentata) habitat modeling: identifying suitable sites for restoration in Shenandoah National Park, Virginia(2013-12-06) Santoro, JenniferSince 2008, The American Chestnut Foundation’s (TACF) Appalachian Trail MEGA-Transect Project has engaged citizen scientists to collect American chestnut occurrence data over the length of the Appalachian Trail. This data helps TACF to locate surviving trees for use in their breeding program and expand their knowledge of chestnuts across the East Coast. However, this dataset is limiting in that it considers only the ridge-top habitat of the trail. To remedy this, we conducted an extensive sampling of side-trails in Shenandoah National Park in order to study more diverse elevation and habitat gradients. Expanding the dataset allows us to draw more informed conclusions about habitat for surviving American chestnuts. To achieve this, I developed a series of species distribution models, including GLM, CART, and Maxent models, based on field observations and spatial data of environmental variables. These predictive distribution models were then combined to generate a comprehensive map of the most likely surviving American chestnut occurrence locations across Shenandoah National Park. Additionally, projections based on future climate were made for the Maxent model to 2050 and 2070 in order to see if habitat for surviving trees might shift in the face of climate warming. Overall, the three species distribution modeling techniques tended to agree on location, but not quantity, of suitable habitat for surviving chestnuts. All models found elevation, sand, and slope to be the most significant habitat predictors in Shenandoah. Climate change models produced only subtle range shifts; as a generalist species, American chestnuts may not face adverse effects of future climate warming. Mapping these results provides valuable information to both Shenandoah National Park and TACF as they continue to search for, study, and restore American chestnuts in the Appalachian forest.Item Open Access Assessing the Potential Effects of Climate Change on Species in the Cumberland Piedmont Network of the National Park Service(2012-04-26) Bruno, Christopher; Hartger, Phil; Mendenhall, Laura; Myron, EmilyIn this study, we evaluate the climate change vulnerability of a subset of key species found in the Cumberland Piedmont Network (CUPN) of the National Park Service (NPS), an ecologically important and diverse region. We developed a list of species of conservation concern (globally and sub-nationally) within each of the fourteen NPS units in the CUPN. Next, we employed NatureServe’s Climate Change Vulnerability Index (CCVI) in order to determine which of those species may be most vulnerable to climate change, based on each species’ 1) direct exposure to climate change, 2) indirect exposure to climate change, 3) sensitivity, and 4) documented/ modeled response to climate change. CCVI results showed a range of vulnerability scores among taxonomic groups, including high vulnerability for mollusks and low vulnerability for migrant songbirds. Furthermore, we found that species of conservation concern were not necessarily those most vulnerable to climate change. Additionally, we modeled the current and projected habitat suitability in 2050 and 2080 for four case study species, three that were assessed by the CCVI to be vulnerable to climate change and one assessed to be presumed stable. We used the software package MaxEnt (chosen modeling method of NatureServe) and the program BIOMOD, which produces habitat suitability estimates using a variety of different algorithms. We combined the results produced by MaxEnt and BIOMOD to create an ensemble projection for each species. This shows areas where all models predict future suitable habitat. Finally, we examined which of the NPS Units within the CUPN were in danger of losing vulnerable species populations under the climate change scenarios we chose. These models predict that key species may disappear from some parks with climate change. This information can be incorporated into regional management and prioritization strategies that increase the long term viability of these species, as well as help NPS land managers better understand which species of conservation concern are likely to be most affected by climate change.Item Open Access Assessing the Potential Effects of Climate Change on Species in the Cumberland Piedmont Network of the National Park Service(2012-04-26) Bruno, Christopher; Hartger, Phil; Mendenhall, Laura; Myron, EmilyIn this study, we evaluate the climate change vulnerability of a subset of key species found in the Cumberland Piedmont Network (CUPN) of the National Park Service (NPS), an ecologically important and diverse region. We developed a list of species of conservation concern (globally and sub-nationally) within each of the fourteen NPS units in the CUPN. Next, we employed NatureServe’s Climate Change Vulnerability Index (CCVI) in order to determine which of those species may be most vulnerable to climate change, based on each species’ 1) direct exposure to climate change, 2) indirect exposure to climate change, 3) sensitivity, and 4) documented/ modeled response to climate change. CCVI results showed a range of vulnerability scores among taxonomic groups, including high vulnerability for mollusks and low vulnerability for migrant songbirds. Furthermore, we found that species of conservation concern were not necessarily those most vulnerable to climate change. Additionally, we modeled the current and projected habitat suitability in 2050 and 2080 for four case study species, three that were assessed by the CCVI to be vulnerable to climate change and one assessed to be presumed stable. We used the software package MaxEnt (chosen modeling method of NatureServe) and the program BIOMOD, which produces habitat suitability estimates using a variety of different algorithms. We combined the results produced by MaxEnt and BIOMOD to create an ensemble projection for each species. This shows areas where all models predict future suitable habitat. Finally, we examined which of the NPS Units within the CUPN were in danger of losing vulnerable species populations under the climate change scenarios we chose. These models predict that key species may disappear from some parks with climate change. This information can be incorporated into regional management and prioritization strategies that increase the long term viability of these species, as well as help NPS land managers better understand which species of conservation concern are likely to be most affected by climate change.Item Open Access Assessing the Potential Effects of Climate Change on Species in the Cumberland Piedmont Network of the National Park Service(2012-04-26) Bruno, Christopher; Hartger, Phil; Mendenhall, Laura; Myron, EmilyIn this study, we evaluate the climate change vulnerability of a subset of key species found in the Cumberland Piedmont Network (CUPN) of the National Park Service (NPS), an ecologically important and diverse region. We developed a list of species of conservation concern (globally and sub-nationally) within each of the fourteen NPS units in the CUPN. Next, we employed NatureServe’s Climate Change Vulnerability Index (CCVI) in order to determine which of those species may be most vulnerable to climate change, based on each species’ 1) direct exposure to climate change, 2) indirect exposure to climate change, 3) sensitivity, and 4) documented/ modeled response to climate change. CCVI results showed a range of vulnerability scores among taxonomic groups, including high vulnerability for mollusks and low vulnerability for migrant songbirds. Furthermore, we found that species of conservation concern were not necessarily those most vulnerable to climate change. Additionally, we modeled the current and projected habitat suitability in 2050 and 2080 for four case study species, three that were assessed by the CCVI to be vulnerable to climate change and one assessed to be presumed stable. We used the software package MaxEnt (chosen modeling method of NatureServe) and the program BIOMOD, which produces habitat suitability estimates using a variety of different algorithms. We combined the results produced by MaxEnt and BIOMOD to create an ensemble projection for each species. This shows areas where all models predict future suitable habitat. Finally, we examined which of the NPS Units within the CUPN were in danger of losing vulnerable species populations under the climate change scenarios we chose. These models predict that key species may disappear from some parks with climate change. This information can be incorporated into regional management and prioritization strategies that increase the long term viability of these species, as well as help NPS land managers better understand which species of conservation concern are likely to be most affected by climate change.Item Open Access Assessing the Potential Effects of Climate Change on Species in the Cumberland Piedmont Network of the National Park Service(2012-04-26) Hartger, Phil, Christopher, Laura, Emily Bruno, Mendenhall, MyronIn this study, we evaluate the climate change vulnerability of a subset of key species found in the Cumberland Piedmont Network (CUPN) of the National Park Service (NPS), an ecologically important and diverse region. We developed a list of species of conservation concern (globally and sub-nationally) within each of the fourteen NPS units in the CUPN. Next, we employed NatureServe’s Climate Change Vulnerability Index (CCVI) in order to determine which of those species may be most vulnerable to climate change, based on each species’ 1) direct exposure to climate change, 2) indirect exposure to climate change, 3) sensitivity, and 4) documented/ modeled response to climate change. CCVI results showed a range of vulnerability scores among taxonomic groups, including high vulnerability for mollusks and low vulnerability for migrant songbirds. Furthermore, we found that species of conservation concern were not necessarily those most vulnerable to climate change. Additionally, we modeled the current and projected habitat suitability in 2050 and 2080 for four case study species, three that were assessed by the CCVI to be vulnerable to climate change and one assessed to be presumed stable. We used the software package MaxEnt (chosen modeling method of NatureServe) and the program BIOMOD, which produces habitat suitability estimates using a variety of different algorithms. We combined the results produced by MaxEnt and BIOMOD to create an ensemble projection for each species. This shows areas where all models predict future suitable habitat. Finally, we examined which of the NPS Units within the CUPN were in danger of losing vulnerable species populations under the climate change scenarios we chose. These models predict that key species may disappear from some parks with climate change. This information can be incorporated into regional management and prioritization strategies that increase the long term viability of these species, as well as help NPS land managers better understand which species of conservation concern are likely to be most affected by climate change.Item Open Access Distribution and Conservation of the Antillean Manatee in Hispaniola(2016) Dominguez Tejo, Haydee MariaAntillean manatees (Trichechus manatus manatus) were heavily hunted in the past throughout the Wider Caribbean Region (WCR), and are currently listed as endangered on the IUCN Red List of Threatened Species. In most WCR countries, including Haiti and the Dominican Republic, remaining manatee populations are believed to be small and declining, but current information is needed on their status, distribution, and local threats to the species.
To assess the past and current distribution and conservation status of the Antillean manatee in Hispaniola, I conducted a systematic review of documentary archives dating from the pre-Columbian era to 2013. I then surveyed more than 670 artisanal fishers from Haiti and the Dominican Republic in 2013-2014 using a standardized questionnaire. Finally, to identify important areas for manatees in the Dominican Republic, I developed a country-wide ensemble model of manatee distribution, and compared modeled hotspots with those identified by fishers.
Manatees were historically abundant in Hispaniola, but were hunted for their meat and became relatively rare by the end of the 19th century. The use of manatee body parts diversified with time to include their oil, skin, and bones. Traditional uses for folk medicine and handcrafts persist today in coastal communities in the Dominican Republic. Most threats to Antillean manatees in Hispaniola are anthropogenic in nature, and most mortality is caused by fisheries. I estimated a minimum island-wide annual mortality of approximately 20 animals. To understand the impact of this level of mortality, and to provide a baseline for measuring the success of future conservation actions, the Dominican Republic and Haiti should work together to obtain a reliable estimate of the current population size of manatees in Hispaniola.
In Haiti, the survey of fishers showed a wider distribution range of the species than suggested by the documentary archive review: fishers reported recent manatee sightings in seven of nine coastal departments, and three manatee hotspot areas were identified in the north, central, and south coasts. Thus, the contracted manatee distribution range suggested by the documentary archive review likely reflects a lack of research in Haiti. Both the review and the interviews agreed that manatees no longer occupy freshwater habitats in the country. In general, more dedicated manatee studies are needed in Haiti, employing aerial, land, or boat surveys.
In the Dominican Republic, the documentary archive review and the survey of fishers showed that manatees still occur throughout the country, and occasionally occupy freshwater habitats. Monte Cristi province in the north coast, and Barahona province in the south coast, were identified as focal areas. Sighting reports of manatees decreased from Monte Cristi eastwards to the adjacent province in the Dominican Republic, and westwards into Haiti. Along the north coast of Haiti, the number of manatee sighting and capture reports decreased with increasing distance to Monte Cristi province. There was good agreement among the modeled manatee hotspots, hotspots identified by fishers, and hotspots identified during previous dedicated manatee studies. The concordance of these results suggests that the distribution and patterns of habitat use of manatees in the Dominican Republic have not changed dramatically in over 30 years, and that the remaining manatees exhibit some degree of site fidelity. The ensemble modeling approach used in the present study produced accurate and detailed maps of manatee distribution with minimum data requirements. This modeling strategy is replicable and readily transferable to other countries in the Caribbean or elsewhere with limited data on a species of interest.
The intrinsic value of manatees was stronger for artisanal fishers in the Dominican Republic than in Haiti, and most Dominican fishers showed a positive attitude towards manatee conservation. The Dominican Republic is an upper middle income country with a high Human Development Index. It possesses a legal framework that specifically protects manatees, and has a greater number of marine protected areas, more dedicated manatee studies, and more manatee education and awareness campaigns than Haiti. The constant presence of manatees in specific coastal segments of the Dominican Republic, the perceived decline in the number of manatee captures, and a more conservation-minded public, offer hope for manatee conservation, as non-consumptive uses of manatees become more popular. I recommend a series of conservation actions in the Dominican Republic, including: reducing risks to manatees from harmful fishing gear and watercraft at confirmed manatee hotspots; providing alternative economic alternatives for displaced fishers, and developing responsible ecotourism ventures for manatee watching; improving law enforcement to reduce fisheries-related manatee deaths, stop the illegal trade in manatee body parts, and better protect manatee habitat; and continuing education and awareness campaigns for coastal communities near manatee hotspots.
In contrast, most fishers in Haiti continue to value manatees as a source of food and income, and showed a generally negative attitude towards manatee conservation. Haiti is a low income country with a low Human Development Index. Only a single dedicated manatee study has been conducted in Haiti, and manatees are not officially protected. Positive initiatives for manatees in Haiti include: protected areas declared in 2013 and 2014 that enclose two of the manatee hotspots identified in the present study; and local organizations that are currently working on coastal and marine environmental issues, including research and education on marine mammals. Future conservation efforts for manatees in Haiti should focus on addressing poverty and providing viable economic alternatives for coastal communities. I recommend a community partnership approach for manatee conservation, paired with education and awareness campaigns to inform coastal communities about the conservation situation of manatees in Haiti, and to help change their perceived value. Haiti should also provide legal protection for manatees and their habitat.
Item Open Access Gap Analysis of Five Orders in Great Smoky Mountain National Park: A Quantification of Inventory Gaps(2016-04-21) Jasny, MicahGlobal biodiversity is currently in a state of crisis with human alterations to the environment exacerbating extinctions so that extinction rates now exceed 1,000 times normal background rates (Lees & Pimm, 2015, Nicholas & Langdon, 2007). To better understand and protect global biodiversity, the All Taxa Biodiversity Inventory (ATBI) project was founded to determine the identity, distribution, and function of every species present within a specific study location (Sharkey, 2001). The most famous ATBI was established in 1998 at Great Smoky Mountain National Park and has since identified over 20,000 species with almost 1,000 species new to science (Discover Life in America, 2014; Nichols & Langdon, 2007; Parker & Bernard, 2006). To help the GSMNP ATBI project use its resources more efficiently, I conducted a taxonomic gap analysis for five orders to identify whether more species may potentially exist within the Park’s boundaries that have yet to be added to species inventories. If inventory gaps were present, I then estimated the total species richness to determine which order had the largest taxonomic gap and should thus be the focus of future sampling efforts. The Park had previously identified five orders that it believed may contain taxonomic gaps: crustaceans, diptera, hemiptera, hymenoptera, and acari. Given species presence locations for these orders, I generated species accumulation curves to determine if taxonomic gaps were present in the Park’s inventories. The species richness modeling program EstimateS was then used to quantify total species richness for each of the focal orders within the Park (Colwell, 2013). Given the estimated total species richness and the number of species previously found by the Park for each order, I was able to quantify the taxonomic gaps in each order’s inventory in terms of the total number of species and the percent of the order identified. To determine where future sampling efforts should be focused to identify the remaining species, I used the species distribution program, Maxent to locate areas of high species richness for each order within the Park (Philips, Dudik, &Shapire, 2010). I compiled 15 environmental predictor layers at a 30m resolution which were uploaded into Maxent along with the presence points of all species that were present at 15 or more locations. Habitat suitability produced by the model was then thresholded and stacked for all species within each order to identify areas of high species overlap. For cases in which the data were spatially structured, bias files were constructed to remove the direct and indirect influences of spatial bias on the models. From the species accumulation curves, it was determined that crustaceans, diptera, hemiptera, and acari all likely had species yet to be found within the Park, while the hymenoptera accumulation curve approached an asymptote at around 550 species. After conducting the species richness analysis, hemiptera was found have the largest gap with about 334 species potentially yet to be identified. However, acari has the largest gap in terms of the percent of the order identified by the Park (45.74%). This Park can now decide whether to view taxonomic gaps in terms of the potential number of species or percent identified. After order-level species distributions were calculated, hemiptera and hymenoptera had the highest richness in the northern and central parts of the Park, diptera and acari were found primarily along streams, and crustaceans had the highest richness in the western parts of the Park. Distance to streams, soil type, vegetation, and slope all play critical roles in defining habitat suitability for these focal orders and all five focal orders can be sampled in the areas in close proximity to Park streams. This analysis identified that past sampling efforts have primarily occurred along trails and roads within the Park so future sampling should be tailored to focus away from these anthropogenic features to avoid under sampling. One of the benefits of this analysis is that its accuracy improves as more sampling is done. With more sample presence locations, both the species richness and species distribution models better reflect reality. Combining species richness and species distribution modeling to structure species inventory efforts will result in more efficient and effective use of resources which will allow the ATBI to better conserve and protect biodiversity within the Park.Item Open Access Invasive Exotic Plants of the Eno River Watershed(2010-04-30T20:02:44Z) Starke, LesleyInvasive exotic species are an international threat to biodiversity. Management of invasive species is divided into three approaches: prevention of introduction outside of native range; eradication of invasions; and containment and control strategies. Prevention is unfortunately limited by accurate predictions and border control measures which are difficult to implement. Similarly, eradication is made difficult due to the fast acting and aggressive behavior of many invasive species, some of which are naturalized for many years before control measures are implemented. This leaves containment and control as management strategies for many managers today. Land protection groups in the United States including non-profit land trusts and governmental agencies – local to national -- address invasive species on nearly all protected lands. I have consulted with the Eno River Association of Durham and Orange counties in North Carolina to address the management of three invasive plant species of concern: tree of heaven (Ailanthus altissima), Chinese privet (Ligustrum sinense), and multiflora rose (Rosa multiflora). After assembling an observational data set of these three species, I used Maxent, a maximum entropy based machine-learning software, to model the potential distribution of each species within the Eno River watershed. Distributions of all three species were best predicted by soil type and distance to rivers. Properties of the Eno River State Park master plan -- a land protection priority list for the Eno River Association and the Eno River State Park -- were analyzed and ranked for the total area and the percent coverage of invasive plants from the modeled distributions.Item Open Access Modeling Point Patterns, Measurement Error and Abundance for Exploring Species Distributions(2010) Chakraborty, AvishekThis dissertation focuses on solving some common problems associated with ecological field studies. In the core of the statistical methodology, lies spatial modeling that provides greater flexibility and improved predictive performance over existing algorithms. The applications involve prevalence datasets for hundreds of plants over a large area in the Cape Floristic Region (CFR) of South Africa.
In Chapter 2, we begin with modeling the categorical abundance data with a multi level spatial model using background information such as environmental and soil-type factors. The empirical pattern is formulated as a degraded version of the potential pattern, with the degradation effect accomplished in two stages. First, we adjust for land use transformation and then we adjust for measurement error, hence misclassification error, to yield the observed abundance classifications. With data on a regular grid over CFR, the analysis is done with a conditionally autoregressive prior on spatial random effects. With around ~ 37000 cells to work with, a novel paralleilization algorithm is developed for updating the spatial parameters to efficiently estimate potential and transformed abundance surfaces over the entire region.
In Chapter 3, we focus on a different but increasingly common type of prevalence data in the so called presence-only setting. We detail the limitations associated with a usual presence-absence analysis for this data and advocate modeling the data as a point pattern realization. The underlying intensity surface is modeled with a point-level spatial Gaussian process prior, after taking into account sampling bias and change in land-use pattern. The large size of the region enforces using an computational approximation with a bias-corrected predictive process. We compare our methodology against the the most commonly used maximum entropy method, to highlight the improvement in predictive performance.
In Chapter 4, we develop a novel hierarchical model for analyzing noisy point pattern datasets, that arise commonly in ecological surveys due to multiple sources of bias, as discussed in previous chapters. The effect of the noise leads to displacements of locations as well as potential loss of points inside a bounded domain. Depending on the assumption on existence of locations outside the boundary, a couple of different models -- island and subregion, are specified. The methodology assumes informative knowledge of the scale of measurement error, either pre-specified or learned from a training sample. Its performance is tested against different scales of measurement error related to the data collection techniques in CFR.
In Chapter 5, we suggest an alternative model for prevalence data, different from the one in Chapter 3, to avoid numerical approximation and subsequent computational complexities for a large region. A mixture model, similar to the one in Chapter 4 is used, with potential dependence among the weights and locations of components. The covariates as well as a spatial process are used to model the dependence. A novel birth-death algorithm for the number of components in the mixture is under construction.
Lastly, in Chapter 6, we proceed to joint modeling of multiple-species datasets. The challenge is to infer about inter-species competition with a large number of populations, possibly running into several hundreds. Our contribution involves applying hierarchical Dirichlet process to cluster the presence localities and subsequently developing measures of range overlap from posterior draws. This kind of simultaneous inference can potentially have implications for questions related to biodiversity and conservation studies. .
Item Open Access Opportunities for enhancing an ecosystem-based approach to pelagic fisheries management in the high seas(2020) Ortuno Crespo, Guillermo AOpen‐ocean fisheries expanded rapidly from the 1960s and currently represent the largest direct stressor on high seas biodiversity and ecosystems. Open-ocean ecological research and the implementation of management actions to mitigate the impacts of fisheries has lagged behind those of coastal and deep-sea environments. I investigate opportunities to enhance a wholistic ecosystem-based approach to high seas fisheries management by: reviewing our understanding of the impacts fisheries across ecological scales, evaluating the gaps and opportunities in the mandates of existing and future governance frameworks and developing methodologies for creating dynamic spatiotemporal management tools to reduce bycatch. Results demonstrate that fisheries are impacting the open-ocean across ecological scales. Results also show that the population trajectories of most non-target species in the high seas are not being monitored by fishing nations, nor relevant fisheries management organizations. A new implementing agreement under the UN to sustainably manage high seas biodiversity could complement the mandates fisheries bodies. There is an opportunity for new technologies and modeling approaches to contribute to the implementation of an ecosystem-based approach to management by generating knowledge on the spatial ecology commercial fisheries and high seas biodiversity. My results show that the distribution of target and non-target species, as well as longline fishing activities are correlated with environmental conditions and that these can be predicted across spatial and temporal scales to inform spatial management of high seas pelagic fishing activities. Implementing an ecosystem-based approach will require embracing a precautionary approach to reduce the bycatch of non-target species, which can be accomplished through spatiotemporal avoidance and improving our monitoring of fisheries impacts across ecological scales.
Item Open Access Predicting conflict over scarce resources: Chimpanzees (Pan troglodytes verus) and Fulɓe pastoralists(2011-04-28) Massa, Brooke E.The western chimpanzee (Pan troglodytes verus) is considered the most endangered subspecies of chimpanzee. The populations living at the furthest extent of its range, in southern Senegal – a country situated directly south of the Sahara Desert - are considered to be nearly extinct. These ‘savanna chimpanzees’ have adapted to living in an arid environment and are now facing more threats to their survival as climate change and deforestation have forced nomadic pastoralists further into their habitat in search of fodder and water. Combining field-collected data on both chimpanzee and pastoralist habitat use with GIS and remote sensing data, I spatially predicted areas of potential habitat conflict among chimpanzees and pastoralists. Using species distribution modeling, I found that large swaths of forested habitat in Bandafassi are predicted to be used by nomadic pastoralists. Their presence is expected in 86 percent of the land which is predicted to be used by chimpanzees. Statistical modeling using the Dirichlet distribution predicted overuse of gallery forests by herders. Since herders remove most of the crowns of 9 species of trees, 7 of which provide important resources for chimpanzees, the impact of herders on chimpanzee resources is likely detrimental. Strategies to protect chimpanzee habitat and increase resources for herders should be considered in community-based conservation projects.Item Open Access Species Distribution Modeling for Bog Turtles (Glyptemys muhlenbergii) in North Carolina(2013-12-06) Dick, KevinThe bog turtle (Glyptemys muhlenbergii) is the smallest turtle species in North America and is listed as a threatened species under the federal Endangered Species Act. Accurate detection of its specialized wetland habitat and subsequent tagging of individuals for monitoring purposes is critical for improving conservation efforts with this species. Parts of the Piedmont region in North Carolina have historically served as habitat for bog turtles, but few populations are now known to occur there. Increases in residential development, agricultural land use, and the draining of wetland areas over the past several decades have likely contributed to their current extirpation from this part of the state. Most wildlife managers no longer survey for bog turtles in most of the Piedmont as efforts are both time and cost prohibitive, and funding generally all allocated for work in counties where they have a better chance of locating bog turtles during a given survey event. Several managers acknowledge that there may still be bog turtles living in the Piedmont, but because of present limitations, there is currently no conservation plan for them. GIS and predictive modeling were used as a low-cost method for locating potential sites within four North Carolina counties that exhibit suitable habitat characteristics for bog turtles. Such predictions may prove useful in documenting new occurrences of bog turtles in both the Piedmont counties of Iredell, Davie, and Davidson, as well as in the higher quality bog turtle habitat regions of Wilkes County. The Maxent distribution model was used as it is capable of producing accurate habitat predictions for species with small sample sizes. A total of 28 areas with species presence and 16 different environmental variables were used in the analysis. The model returned several sites within Wilkes County exhibiting higher levels of predicted suitability, and a smaller number of sites within Iredell County with moderate levels of suitability. The predicted sites in Iredell County were previously unknown to wildlife managers, and may help to direct future survey work in those locations. If these model predictions can be translated to positive detection of turtles in the field, spatial modeling work of this kind may begin to play a larger role in the conservation efforts for the species.